Many different approaches are known to uniquely identify and authenticate objects, including labeling and tagging strategies using serial numbers, bar codes, holographic labels, RFID tags, and hidden patterns using security inks or special fibers. All of these methods can be duplicated, and many add substantial costs to the production of the goods sought to be protected. Physical labels and tags are also themselves at risk of being lost, stolen, or counterfeited.
Other known techniques for object identification or authentication rely on the comparison of bitmaps of images of objects. Referring now to FIG. 8, an image of an object is captured and stored for reference. The whole image is stored, although it may be compressed for efficiency. When a new object is encountered, an image is captured of the new object and compared to the original image, using XOR or similar algorithms. If there are no (or only statistically insignificant) differences, the images are declared a match and the object is authenticated. Further, FFT or similar transforms may be used to generate a “digital signature” of the image that can be used for comparison. See FIG. 9. However, as in the previous case the same method is used, i.e. the resultant bitmapped image is compared with another bitmapped image, and if the pixels match the object is authenticated. Such methods are disclosed in U.S. Pat. No. 7,680,306 to Boutant, et al. Bitmapped techniques have limitations that render them unusable in many real world applications, such limitations consisting of, for example, inefficiencies due to file sizes, difficulties presented by variable lighting and orientation of images, and the inability to authenticate worn, damaged, or otherwise altered objects.